code: def test_two_point_correlation_numerical_consistency(
      global_random_seed,
  ):
      # Test consistency with respect to the `two_point_correlation` method
      X_64, X_32, Y_64, Y_32 = get_dataset_for_binary_tree(
          random_seed=global_random_seed
      )
  
      bt_64 = BallTree64(X_64, leaf_size=10)
      bt_32 = BallTree32(X_32, leaf_size=10)
  
      r = np.linspace(0, 1, 10)
  
      counts_64 = bt_64.two_point_correlation(Y_64, r=r, dualtree=True)
      counts_32 = bt_32.two_point_correlation(Y_32, r=r, dualtree=True)
      assert_allclose(counts_64, counts_32)
  
file_path: scikit-learn/sklearn/neighbors/tests/test_ball_tree.py
imports: import itertools
  import numpy
  import pytest
  from numpy.testing import assert_allclose, assert_array_almost_equal, assert_equal
  from sklearn.neighbors._ball_tree import BallTree, BallTree32, BallTree64
  from sklearn.utils import check_random_state
  from sklearn.utils._testing import _convert_container
  from sklearn.utils.validation import check_array
label_desc: Use image node_id 9 for calling a global function with example usage: test_two_point_correlation_numerical_consistency(global_random_seed) without return types